Arbol builds scalable, reliable ETL infrastructure to power global climate intelligence
Arbol needed a unified framework to manage climate data from global sources and accelerate risk analytics for its parametric insurance platform.
About
Arbol is a global climate risk and parametric insurance platform that helps organizations manage financial exposure to weather and climate volatility. Its mission is to make climate risk coverage more accessible, objective, and data-driven.
As climate-related events grow in frequency and severity, Arbol’s technology uses real-time environmental data and smart contracts to provide fast, automated payouts—reducing human error and latency.
To support its expanding climate intelligence network, Arbol partnered with Lumenalta to build a scalable cloud-based ETL and data governance framework designed to improve reliability, data quality, and developer efficiency.
95%
faster settlements vs traditional claims
80+
countries with active coverage
100%
automated payout logic via smart contracts
Challenge
Arbol’s ability to deliver reliable climate analytics depended on the speed and accuracy of its data pipelines. However, collecting and standardizing global datasets presented significant technical and operational challenges.
Key challenges included:
- Inconsistent ETL processes across regions and data sources
- Fragmented data formats from international organizations and agencies
- Lack of a standardized framework for building and maintaining ETLs
- Limited centralized access slowing analysis and collaboration
- Unstructured APIs without clear naming or testing conventions
- Inefficient onboarding of new datasets and markets
- Increased operational complexity impacting development velocity
Without modernization, Arbol’s teams faced rising technical debt and slower time-to-market for new insurance products.
Solution
Lumenalta embedded with Arbol’s engineering team to design and implement a reusable ETL and data governance framework that could scale across datasets, geographies, and product lines.
First, Lumenalta standardized climate data ingestion from multiple global sources—such as government and institutional datasets—into a unified cloud-based structure. This ensured reliability, consistency, and faster access to real-time and historical data.
Next, a reusable ETL code library was built using Python and deployed through AWS infrastructure, enabling faster deployment of new pipelines and simplifying onboarding for new datasets. The framework integrated data validation, logging, and monitoring, ensuring dependable operations at scale.
Finally, Lumenalta introduced standardized RESTful APIs and a defined testing strategy using Pytest and GitHub workflows. These changes improved developer efficiency, reduced integration errors, and supported consistent internal collaboration across teams.
Results
The engagement produced a robust, cloud-native foundation that strengthened Arbol’s data reliability, accelerated product development, and empowered teams to scale climate risk modeling globally.
Key results include:
- Centralized, cloud-based data platform supporting global climate intelligence
- Reusable ETL framework simplifying onboarding of new datasets and countries
- Standardized RESTful APIs improving data quality and internal collaboration
- Defined API testing strategy ensuring reliability and consistency
- Faster ETL development for new regions and data sources
- Improved data accessibility and reduced operational complexity
- Framework built for continuous expansion and scalable climate risk analysis
The new system enables Arbol to accelerate innovation in parametric insurance—delivering accurate, real-time insights to clients worldwide.
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